MEPI-MS16

Models of COVID-19 Vaccination, Non-Pharmaceutical Interventions, and Relaxation

Wednesday, June 16 at 07:45pm (PDT)
Thursday, June 17 at 03:45am (BST)
Thursday, June 17 11:45am (KST)

SMB2021 Follow Wednesday (Thursday) during the "MS16" time block.

Note: this minisymposia has multiple sessions. The second session is MS11-MEPI (click here). The third session is MS20-MEPI (click here).

Jane Heffernan (York University, Canada), Miranda Teboh Ewungkem (Lehigh University, USA), Zhilan Feng (Purdue University, USA), John Glasser (Centres for Disease Control, USA)

Description:

At present, health policymakers are focused on allocating available vaccine among healthcare, other essential workers, and vulnerable segments of their populations. As immunity to SARS-CoV-2 increases, however, their attention will turn increasingly to assessments of the relative effectiveness of non-pharmaceutical interventions so that the least effective ones, especially those with adverse economic impact, and possibly eventually all, can be relaxed. As transmission modeling can inform such decisions, we will invite several speakers to share their recent work to address question on vaccination, NPI interventions, and relaxation.

Jeff Shaman

(Columbia University, USA)

"Overall Burden and Characteristics of COVID-19 in the US"

The COVID-19 pandemic disrupted health systems and economies throughout the world during 2020 and was particularly devastating for the United States, which experienced the highest numbers of reported cases and deaths during 2020. Many of epidemiological features responsible for observed rates of morbidity and mortality have not been comprehensively quantified. Here we use a data-driven model-inference approach to simulate the pandemic at county-scale in the United States during 2020 and estimate critical, time-varying epidemiological properties underpinning the dynamics of the virus, in particular the ascertainment rate, population susceptibility, community infection rates and the infection fatality rate. The results provide a county-resolved depiction of conditions until the end of 2020 when COVID-19 vaccine administration began. The implications for ongoing control of the virus are also investigated.

David Dick

(York University, Canada)

"A Model of COVID-19 Vaccination and Waning Immunity in Canada"

We have developed an age- and immunity-structured model of COVID-19 infection and vaccination. The model assumes rates of waning immunity from infection and vaccination. It also includes different non-pharmaceutical interventions, including work-from-home, school closure, social distancing and mask wearing. In this talk I will discuss different outcomes of a Canadian-informed COVID-19 vaccination program given different types of vaccines and rollout strategies. I will also discuss scenarios for relaxation and mitigation strategies needed to inhibit a Fall 2021 resurgence.

Toby Brett

(University of Georgia, USA)

"How mathematical modeling reveals the impracticality of COVID-19 herd immunity strategies"

Confronted with escalating COVID-19 outbreaks, countries at the leading edge of the pandemic have resorted to imposing drastic social distancing measures, with serious societal and economic repercussions. Establishing herd immunity in a population by allowing the epidemic to spread, while mitigating the negative health impacts of COVID-19, has presented a tantalizing resolution to the crisis. Using an ODE-based transmission model, parameterized to simulate SARS-CoV-2 transmission in the United Kingdom, we assessed the long-term prospects of achieving herd immunity without mass vaccination. We studied a range of different nonpharmaceutical intervention scenarios incorporating social distancing applied to differing age groups using a combination of numerical simulations and analytical techniques. Our modeling confirmed that suppression of SARS-CoV-2 transmission is possible with plausible levels of social distancing over a period of months, consistent with observed trends. Our findings show that achieving herd immunity without overwhelming hospital capacity leaves little room for error. Intervention levels must be carefully manipulated in an adaptive manner for an extended period, despite acute sensitivity to poorly quantified epidemiological factors. Specifically, we found that 1) social distancing must initially reduce the transmission rate to within a narrow range, 2) to compensate for susceptible depletion, the extent of social distancing must be adaptive over time in a precise yet unfeasible way, and 3) social distancing must be maintained for an extended period to ensure the healthcare system is not overwhelmed. Such fine-tuning of social distancing renders this strategy impractical.

Daniel Larremore

(University of Colorado, USA)

"Vaccine prioritization strategies with age, serostatus, and immunosenescence"

Limited initial supply of SARS-CoV-2 vaccine raised the question of how to prioritize available doses. One might reason, intuitively, that doses should be prioritized to directly protect those who are most vulnerable. Yet one might also intuitively argue that we should use vaccination as a means to break chains of transmission by prioritizing early doses to those most responsible for transmission, thereby indirectly protecting the vulnerable by reducing prevalence. Unfortunately, these two intuitive solutions make orthogonal recommendations. Here, we introduce a family of mixed discrete and differential equation models to resolve the tension between these recommendations, and compare five age-stratified vaccine prioritization strategies. By considering the demographics and contact patterns in the country of interest, transmission rates, vaccine properties, and the accumulated immunity in the population due to prior infection with SARS-CoV-2, we show how one can use differential equation models to quantify the tradeoffs between vaccine rollout strategies in a context-specific ways. We also highlight ways in which these models can help ameliorate existing pandemic-related inequities in access to healthcare and protection. In this talk, we will cover both the high-level results and recommendations, as well as vaccine-related modeling choices that complicate the more typical and standard 'SIR' type disease model.

Hosted by SMB2021 Follow

Virtual conference of the Society for Mathematical Biology, 2021.